Abstract: We study robust and efficient distributed algorithms for searching, storing, and maintaining data in dynamic Peer-to-Peer (P2P) networks. P2P networks are highly dynamic networks that experience heavy node churn (i.e., nodes join and leave the network continuously over time). Our goal is to guarantee, despite high node churn rate, that a large number of nodes in the network can store, retrieve, and maintain a large number of data items. Our main contributions are fast randomized distributed algorithms that guarantee the above with high probability even under high adversarial churn. In particular, we present the following main results:
1. A randomized distributed search algorithm that with high probability guarantees that searches from as many as n−o(n) nodes (n is the stable network size) succeed in O(logn)- rounds despite O(n/log^(1+δ) n) churn, for any small constant δ >= 0, per round. We assume that the churn is controlled by an oblivious adversary (that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm).
2. A storage and maintenance algorithm that guarantees, with high probability, data items can be efficiently stored (with only Θ(logn) copies of each data item) and maintained in a dynamic P2P network with churn rate up to O(n/log^(1+δ) n) per round. Our search algorithm together with our storage and maintenance algorithm guarantees that as many as n − o(n) nodes can efficiently store, maintain, and search even under O(n/log^(1+δ) n) churn per round. Our algorithms require only polylogarithmic in n bits to be processed and sent (per round) by each node. To the best of our knowledge, our algorithms are the ﬁrst-known, fully-distributed storage and search algorithms that provably work under highly dynamic settings (i.e., high churn rates per step). Furthermore, they are localized (i.e., do
not require any global topological knowledge) and scalable. A technical contribution of this paper, which may be of independent interest, is showing how random walks can be provably used to derive scalable distributed algorithms in dynamic networks with adversarial node churn.
Guests: Gopal Pandurangan and Peter Robinson
Host: Stefan Schmid